Triple
T33324449
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Siegfried & Roy |
E853226
|
entity |
| Predicate | notableAnimalUsed |
P16495
|
FINISHED |
| Object | white tiger |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: white tiger | Statement: [Siegfried & Roy, notableAnimalUsed, white tiger]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableAnimalUsed Context triple: [Siegfried & Roy, notableAnimalUsed, white tiger]
-
A.
usedAnimal
chosen
Indicates that one entity employed or exploited an animal for a particular purpose or activity.
-
B.
notableCreatureStudied
Indicates that a particular creature has been the subject of significant study or research by the referenced entity.
-
C.
involvedAnimal
Indicates that an animal participates in, is affected by, or is otherwise directly connected to the event or situation described.
-
D.
usesAnimalCarcass
Indicates that an entity makes use of an animal’s dead body or its remains for some purpose.
-
E.
notableSpecies
Indicates that the subject is known for, or significantly associated with, the specified species.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69f349685f088190b8fda44083a018a9 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a037c8ae0248190b7e2ce4bf852c22d |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379f338b881908e5593e45d764f4d |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:33 a.m.